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Bamboo, a renewable resource with rapid growth and an impressive height-to-diameter ratio, faces mechanical instability due to its slender structure. Despite this, bamboo maintains its posture without breaking in its battle against environmental and gravitational forces. But what drives this motor function in bamboo? This study subjected Moso bamboo (Phyllostachys edulis) to gravitational stimulation, compelling it to grow at a 45° angle instead of upright. Remarkably, the artificially inclined bamboo exhibited astonishing shape control and adjustment capabilities. The growth strain was detected at both macroscopic and microscopic levels, providing evidence for the presence of internal stress, namely growth stress. The high longitudinal tensile stress on the upper side, along with a significant asymmetry in stress distribution in tilted bamboo, plays a pivotal role in maintaining its mechanical stability. Drawing upon experimental findings, it can be deduced that the growth stress primarily originates from the broad layers of fiber cells. Bamboo could potentially regulate the magnitude of growth stress by modifying the number of fiber cell layers during its maturation process. Additionally, the microfibril angle and lignin disposition may decisively influence the generation of growth stress.
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Plasmonic nanosensors and the dynamic control of light fields are of the utmost significance in the field of micro- and nano-optics. Here, our study successfully demonstrates a plasmonic nanosensor in a compact coupled resonator system and obtains the pressure-induced transparency phenomenon for the first time to our knowledge. The proposed structure consists of a groove and slot cavity coupled in the metal-insulator-metal waveguide, whose mechanical and optical characteristics are investigated in detail using the finite element method. Simulation results show that we construct a quantitative relationship among the resonator deformation quantity, the applied pressure variation, and the resonant wavelength offset by combining the mechanical and optical properties of the proposed system. The physical features contribute to highly efficient plasmonic nanosensors for refractive index and optical pressure sensing with sensitivity of 1800â nm/RIU and 7.4â nm/MPa, respectively. Furthermore, the light waves are coupled to each other in the resonators, which are detuned due to the presence of pressure, resulting in the pressure-induced transparency phenomenon. It is noteworthy to emphasize that, unlike previously published works, our numerical results take structural deformation-induced changes in optical properties into account, making them trustworthy and practical. The proposed structure introduces a novel, to the best of our knowledge, approach for the dynamic control of light fields and has special properties that can be utilized for the realization of various integrated components.
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Using the 2010-2019 Comprehensive Survey of Living Conditions (CSLC) conducted in Japan, we examined the impact of long working hours on mental health in Japan while addressing the endogeneity issue arising from non-random selection bias. We assessed the variations in the effects of long working hours on mental health across different groups. The results show that first, individuals working longer hours (55 h or more per week) exhibited a higher likelihood of developing mental illness than those working regular hours or fewer hours. Second, the negative effect of long working hours on mental health is more pronounced among non-regular workers than among regular workers. Third, the effect of long working hours on mental health varies among different demographic groups, with a greater impact observed among women, managers, non-regular workers, employees in small- or large-sized firms, and those in smaller cities compared to their counterparts. Thus, to enhance worker productivity, the Japanese government should address the issue of long working hours to improve employees' mental well-being. Initiatives aimed at promoting work-life balance, family-friendly policies, and measures to ameliorate working conditions are expected to help mitigate the challenges associated with long working hours and mental health issues, especially among non-regular workers.
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Salud Mental , Humanos , Japón , Salud Mental/estadística & datos numéricos , Femenino , Adulto , Masculino , Persona de Mediana Edad , Encuestas y Cuestionarios , Adulto Joven , Trastornos Mentales/epidemiología , Tolerancia al Trabajo Programado/psicologíaRESUMEN
Among the various physiological signals, electrocardiogram (ECG) is a valid criterion for the classification of various exercise fatigue. In this study, we combine features extracted by deep neural networks with linear features from ECG and heart rate variability (HRV) for exercise fatigue classification. First, the ECG signals are converted into 2-D images by using the short-term Fourier transform (STFT), and image features are extracted by the visual geometry group (VGG) . The extracted image and linear features of ECG and HRV are sent to the different types of classifiers to distinguish distinct exercise fatigue level. To validate performance, the proposed methods are tested on (i) an open-source EPHNOGRAM dataset and (ii) a self-collected dataset (n = 51). The results reveal that the classification based on the concatenated features has the highest accuracy, and the calculation time of the system is also significantly reduced. This demonstrates that the proposed novel hybrid approach can be used to assist in improving the accuracy and timeliness of exercise fatigue classification in a real-time exercise environment. The experimental results show that the proposed method outperforms other recent state-of-the-art methods in terms of accuracy 96.90%, sensitivity 96.90%, F1-score of 0.9687 in EPHNOGRAM and accuracy 92.17%, sensitivity 92.63%, F1-score of 0.9213 in self-collected dataset.
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Electrocardiografía , Ejercicio Físico , Fatiga , Frecuencia Cardíaca , Procesamiento de Señales Asistido por Computador , Máquina de Vectores de Soporte , Humanos , Electrocardiografía/métodos , Frecuencia Cardíaca/fisiología , Ejercicio Físico/fisiología , Fatiga/fisiopatología , Fatiga/diagnóstico , Redes Neurales de la Computación , Masculino , Algoritmos , AdultoRESUMEN
Protein phosphorylation is a significant post-translational modification that plays a decisive role in the occurrence and development of diseases. However, the rapid and accurate identification of phosphoproteins remains challenging. Herein, a high-throughput sensor array has been constructed based on a magnetic bimetallic nanozyme (Fe3O4@ZNP@UiO-66) for the identification and discrimination of phosphoproteins. Attributing to the formation of Fe-Zr bimetallic dual active centers, the as-prepared Fe3O4@ZNP@UiO-66 exhibits enhanced peroxidase-mimicking catalytic activity, which promotes the electron transfer from Zr center to Fe(II)/Fe(III). The catalytic activity of Fe3O4@ZNP@UiO-66 can be selectively inhibited by phosphoproteins due to the strong interaction between phosphate groups and Zr centers, as well as the ultra-robust antifouling capability of zwitterionic dopamine nanoparticle (ZNP). Considering the diverse binding affinities between various proteins with the nanozyme, the catalytic activity of Fe3O4@ZNP@UiO-66 can be changed to various degree, leading to the different absorption responses at 420 nm in the hydrogen peroxide (H2O2) - 2, 2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) system. By simply extracting different absorbance intensities at various time points, a sensor array based on reaction kinetics for the discrimination of phosphoproteins from other proteins is constructed through linear discriminant analysis (LDA). Besides, the quantitative determination of phosphoproteins and identification of protein mixtures have been realized. Further, based on the differential level of phosphoproteins in cells, the differentiation of cancer cells from normal cells can also be implemented by utilizing the proposed sensor array, showing great potential in disease diagnosis.
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Técnicas Biosensibles , Peróxido de Hidrógeno , Neoplasias , Fosfoproteínas , Circonio , Técnicas Biosensibles/métodos , Humanos , Fosfoproteínas/química , Fosfoproteínas/metabolismo , Peróxido de Hidrógeno/química , Circonio/química , Peroxidasa/química , Dopamina/química , Límite de Detección , Materiales Biomiméticos/química , CatálisisRESUMEN
This study examines the relationship between gastrointestinal symptoms in patients with functional gastrointestinal disorders (FGIDs) and type D personality traits, as well as emotion regulation strategies. Analyzing a diverse group of FGID patients, we uncover significant effects of gender and age on gastrointestinal symptoms. Negative Affectivity emerges as a key predictor, positively associated with symptom severity, whereas Social Inhibition correlates negatively with Abdominal Pain. Additionally, our findings suggest that the expressive suppression strategy predicts heightened gastrointestinal symptoms, whereas cognitive reappraisal predicts lower levels of certain symptoms. These findings provide valuable insights for precise diagnosis and tailored treatments of FGIDs. Further research is warranted to explore underlying mechanisms and inform evidence-based interventions.
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ß-Amyloid peptide (Aß) deposition in the brain is an important pathological change in Alzheimer's disease (AD). Insulin-degrading enzyme (IDE), which is regulated transcriptionally by peroxisome proliferator-activated receptor γ (PPARγ), is able to proteolyze Aß. One of the members of the MAPK family, ERK, is able to mediate the phosphorylation of PPARγ at Ser112, thereby inhibiting its transcriptional activity. Ginsenoside Rg1 is one of the active ingredients in the natural medicine ginseng and has inhibitory effects on Aß production. The present study was designed to investigate whether ginsenoside Rg1 is able to affect the regulation of PPARγ based on the expression of its target gene, IDE, and whether it is able to promote Aß degradation via inhibition of the ERK/PPARγ phosphorylation pathway. In the present study, primary cultured rat hippocampal neurons were treated with Aß1-42, ginsenoside Rg1 and the ERK inhibitor PD98059, and subsequently TUNEL staining was used to detect the level of neuronal apoptosis. ELISA was subsequently employed to detect the intra- and extracellular Aß1-42 levels, immunofluorescence staining and western blotting were used to detect the translocation of ERK from the cytoplasm to the nucleus, immunofluorescence double staining was used to detect the co-expression of ERK and PPARγ, and finally, western blotting was used to detect the phosphorylation of PPARγ at Ser112 and IDE expression. The results demonstrated that ginsenoside Rg1 or PD98059 were able to inhibit primary cultured hippocampal neuron apoptosis induced by Aß1-42 treatment, reduce the levels of intra- and extraneuronal Aß1-42 and inhibit the translocation of ERK from the cytoplasm to the nucleus. Furthermore, administration of ginsenoside Rg1 or PD98059 resulted in attenuated co-expression of ERK and PPARγ, inhibition of phosphorylation of PPARγ at Ser112 mediated by ERK and an increase in IDE expression. In addition, the effects when PD98059 to inhibit ERK followed by treatment with ginsenoside Rg1 were found to be more pronounced than those when using PD98059 alone. In conclusion, ginsenoside Rg1 was demonstrated to exert neuroprotective effects on AD via inhibition of the ERK/PPARγ phosphorylation pathway, which led to an increase in IDE expression, the promotion of Aß degradation and the decrease of neuronal apoptosis. These results could provide a theoretical basis for the clinical application of ginsenoside Rg1 in AD.
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Sestrin2 (SESN2) is a stress-inducible protein and acts as a neuroprotective regulator. The present study aimed to explore the antidepressant activity of SESN2 and its relevant mechanism. Depression mouse model was established by chronic unpredictable mild stress (CUMS) for a successive 5 weeks. Behaviors tests were conducted to examine depressive-like behaviors including sugar preference test, tail suspension test and open field test. The expression of SESN2 and ferroptosis-related proteins was examined by western blot. The production of cytokines was measured by ELISA. Iron deposition was assessed using Prussian blue staining and Fe 2+ content was measured using commercial kits. Lipid peroxidation was evaluated by thiobarbituric acid reactive substances assay. BV-2 cells were treated with LPS to induce microglial activation, which was evaluated by the iba-1 level adopting immunofluorescence assay. The ferroptosis inducer Erastin was adopted for the pretreatment in BV-2 cells to conduct a rescue experiment. SESN2 was downregulated in CUMS-induced mice, and SESN2 overexpression dramatically ameliorated CUMS-induced depression-like behaviors. Meanwhile, SESN2 reduced the production of pro-inflammatory cytokines and iba-1 level in hippocampus of CUMS mice, as well as reducing iron deposition and lipid peroxidation, demonstrating that SESN2 reduced microglial activation, neuroinflammation and ferroptosis in CUMS mice. Similarly, SESN2 also restricted iba-1 level, pro-inflammatory cytokines production, and ferroptosis in LPS-induced BV-2 cells, which was partly reversed by additional treatment of Erastin. These findings suggest that SESN2 possesses potent antidepressant property through inhibiting ferroptosis and neuroinflammation.
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Ferroptosis , Enfermedades Neuroinflamatorias , Animales , Ratones , Antidepresivos/farmacología , Antidepresivos/uso terapéutico , Antidepresivos/metabolismo , Citocinas/metabolismo , Depresión/tratamiento farmacológico , Depresión/etiología , Depresión/metabolismo , Modelos Animales de Enfermedad , Hipocampo/metabolismo , Hierro/metabolismo , Lipopolisacáridos/toxicidad , Estrés Psicológico/metabolismoRESUMEN
This study aimed to reveal harm of exposure to indoor air pollution to cognitive function through "gut-brain-axis" among rural elderly residents. There were 120 participants recruited in rural villages of northwest China from December 2021 to February 2022. The cognitive level was assessed by eight-item ascertain dementia (AD) questionnaire, and indoor air pollution exposure was measured by air quality sensor. Inflammatory cytokines and oxidative stress-related index were detected in blood serum. Fecal samples were collected for gut microbiota analysis. The 120 participants were divided into impaired cognition (AD8) (81/67.5%) and cognition normal (NG) (39/32.5%). And there had more female in AD8 (FAD) (55/67.9%) than NG (FNG) (18/46.2%) (P = 0.003). Exposure of air pollution in FAD was higher than FNG (PM1, PM2.5, PM10, P < 0.001; NO2, P < 0.001; CO, P = 0.014; O3, P = 0.002). The risk of cognitive impairment increases 6.8%, 3.6%, 2.6%, 11%, and 2.4% in female for every 1 µg/m3 increased in exposure of PM1, PM2.5, PM10, NO2, and O3, separately. And GSH-Px and T-SOD in FAD were significantly lower than the FNG group (P = 0.011, P = 0.019). Gut microbiota in FAD is disordered with lower richness and diversity. Relative abundance of core bacteria Faecalibacterium (top 1 genus) in FAD was reduced (13.65% vs 19.81%, P = 0.0235), while Escherichia_Shigella and Akkermansia was increased. Correlation analysis showed Faecalibacterium was negatively correlated with age, and exposure of O3, PM1, PM2.5, and PM10; Akkermansia and Monoglobus were positively correlated with exposure of PM1, PM2.5 and PM10; Escherichia_Shigella was significantly positively correlated with NO2. Indoor air pollution exposure impaired cognitive function in elderly people, especially female, which may cause systemic inflammation, dysbiosis of the gut microbiota, and ultimately leading to early cognitive impairment through the gut-brain axis.
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Contaminantes Atmosféricos , Contaminación del Aire , Disfunción Cognitiva , Microbioma Gastrointestinal , Humanos , Femenino , Anciano , Contaminantes Atmosféricos/análisis , Material Particulado/análisis , Eje Cerebro-Intestino , Dióxido de Nitrógeno/análisis , Exposición a Riesgos Ambientales/análisis , Contaminación del Aire/análisis , Polvo/análisis , Disfunción Cognitiva/epidemiología , China , CogniciónRESUMEN
A method was established for the simultaneous detection of 12 prohibited veterinary drugs, including ß2-receptor agonists, nitrofuran metabolites, nitroimidazoles, chlorpromazine, and chloramphenicol, in pig urine. The sample was pretreated by enzymolysis, acid hydrolysis/derivatization, and liquid-liquid extraction combined with solid-phase extraction. Detection was performed using ultra high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Ammonium acetate solution (0.2 mol/L, 4.5 mL) and ß-glucuronidase/aryl sulfatase (40 µL) were added to the sample, which was subsequently enzymolized at 37 â for 2 h. Then, 1.5 mL of 1.0 mol/L hydrochloric acid solution and 100 µL of 0.1 mol/L o-nitrobenzaldehyde solution were added to the sample. The mixture was incubated at 37 â for 16 h, and the analytes were extracted with 8 mL of ethyl acetate by liquid-liquid extraction. The lower aqueous phase obtained after extraction was extracted and purified using a mixed cation-exchange solid-phase extraction column. The extracts were combined, the extraction solution was blow-dried with nitrogen, and the residue was redissolved for determination. The samples were analyzed under multiple-reaction monitoring mode with both positive and negative electrospray ionization, and quantified using an isotope internal standard method. The correlation coefficients (r) of the 12 compounds were >0.99. The limits of detection (LODs) and quantification (LOQs) of chloramphenicol were 0.05 and 0.1 µg/L, respectively, and the LODs and LOQs of the other compounds were 0.25 and 0.5 µg/L, respectively. The mean recoveries and RSDs at 1, 2, and 10 times the LOQ were 83.6%-115.3% and 2.20%-12.34%, respectively. The proposed method has the advantages of high sensitivity, good stability, and accurate quantification; thus, it is suitable for the simultaneous determination of the 12 prohibited veterinary drug residues in pig urine.
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Residuos de Medicamentos , Espectrometría de Masas en Tándem , Drogas Veterinarias , Animales , Espectrometría de Masas en Tándem/métodos , Porcinos , Cromatografía Líquida de Alta Presión/métodos , Drogas Veterinarias/orina , Drogas Veterinarias/análisis , Residuos de Medicamentos/análisis , Cloranfenicol/orina , Cloranfenicol/análisisRESUMEN
Catalase (CAT), a ubiquitous enzyme in all oxygen-exposed organisms, effectively decomposes hydrogen peroxide (H2O2), a harmful by-product, into water and oxygen, mitigating oxidative stress and cellular damage, safeguarding cellular organelles and tissues. Therefore, CAT plays a crucial role in maintaining cellular homeostasis and function. Owing to its pivotal role, CAT has garnered considerable interest. However, many challenges arise when used, especially in multiple practical processes. "Immobilization", a widely-used technique, can help improve enzyme properties. CAT immobilization offers numerous advantages, including enhanced stability, reusability, and facilitated downstream processing. This review presents a comprehensive overview of CAT immobilization. It starts with discussing various immobilization mechanisms, support materials, advantages, drawbacks, and factors influencing the performance of immobilized CAT. Moreover, the review explores the application of the immobilized CAT in various industries and its prospects, highlighting its essential role in diverse fields and stimulating further research and investigation. Furthermore, the review highlights some of the world's leading companies in the field of the CAT industry and their substantial potential for economic contribution. This review aims to serve as a discerning, source of information for researchers seeking a comprehensive cutting-edge overview of this rapidly evolving field and have been overwhelmed by the size of publications.
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Catalasa , Enzimas Inmovilizadas , Enzimas Inmovilizadas/química , Enzimas Inmovilizadas/metabolismo , Catalasa/metabolismo , Catalasa/química , Animales , Peróxido de Hidrógeno/metabolismo , Peróxido de Hidrógeno/química , Estabilidad de Enzimas , HumanosRESUMEN
Acute myocardial infarction stands as a prominent cause of morbidity and mortality worldwide1-6. Clinical studies have demonstrated that the severity of cardiac injury following myocardial infarction exhibits a circadian pattern, with larger infarct sizes and poorer outcomes in patients experiencing morning onset myocardial infarctions7-14. However, the molecular mechanisms that govern circadian variations of myocardial injury remain unclear. Here, we show that BMAL114-20, a core circadian transcription factor, orchestrates diurnal variability in myocardial injury. Unexpectedly, BMAL1 modulates circadian-dependent cardiac injury by forming a transcriptionally active heterodimer with a non-canonical partner, hypoxia-inducible factor 2 alpha (HIF2A)6,21-23, in a diurnal manner. Substantiating this finding, we determined the cryo-EM structure of the BMAL1/HIF2A/DNA complex, revealing a previously unknown capacity for structural rearrangement within BMAL1, which enables the crosstalk between circadian rhythms and hypoxia signaling. Furthermore, we identified amphiregulin (AREG) as a rhythmic transcriptional target of the BMAL1/HIF2A heterodimer, critical for regulating circadian variations of myocardial injury. Finally, pharmacologically targeting the BMAL1/HIF2A-AREG pathway provides effective cardioprotection, with maximum efficacy when aligned with the pathway's circadian trough. Our findings not only uncover a novel mechanism governing the circadian variations of myocardial injury but also pave the way for innovative circadian-based treatment strategies, potentially shifting current treatment paradigms for myocardial infarction.
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This research presents a comprehensive analysis of deep neural network models (DNNs) for the precise prediction of Vickers hardness (HV) in nitrided and carburized M50NiL steel samples, with hardness values spanning from 400 to 1000 HV. By conducting rigorous experimentation and obtaining corresponding nanoindentation data, we evaluated the performance of four distinct neural network architectures: Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory network (LSTM), and Transformer. Our findings reveal that MLP and LSTM models excel in predictive accuracy and efficiency, with MLP showing exceptional iteration efficiency and predictive precision. The study validates models for broad application in various steel types and confirms nanoindentation as an effective direct measure for HV hardness in thin films and gradient-variable regions. This work contributes a validated and versatile approach to the hardness assessment of thin-film materials and those with intricate microstructures, enhancing material characterization and potential application in advanced material engineering.